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Keyword: ExtractionEEG Feature Extraction based on Fast Fourier Transform and Wavelet Analysis for Classification of Mental Stress Levels using Machine Learning
Mental stress assessment remains riddled with biases caused by subjective reports and individual differences across societal backgrounds. To objectively determine the presence or absence of mental stress, there is a need to move away from the traditional subjective methods of self-report questionnaires and interviews. Previously, it has been evidence that EEG Oscillations can discriminate mental…
Read MoreExtraction of Psychological Symptoms and Instantaneous Respiratory Frequency as Indicators of Internet Addiction Using Rule-Based Machine Learning
Internet addiction (IA) has adverse effects on psychophysiological responses, interpersonal relationships, and academic and occupational performance. IA detection has received increasing attention. Although questionnaires enable long-term assessment (over 6 months) and physiological measurements to aid the short-term evaluation (over 2 min) of IA, the lack of algorithms results in an inability to detect IA in…
Read MoreNumerical Analysis for Feature Extraction and Evaluation of 3D Sickness
Artificial intelligence (AI) systems have been applied not only to numerical simulations of the economical sequences but also to the bio-signal, for instance, the statokinesigrams (SKGs). According to the nonlinear analysis of the bio-signal, we have considered that the motion process of the body sway is more random than that of the other bio-signal. In…
Read MoreObserver-Based Method of Feature Extraction for the Fault Detection of Permanent Magnet Synchronous Motors
This paper presents a new observer-based method which deals with the extraction of amplitude of characteristic frequencies for the fault diagnosis in permanent magnet synchronous motors (PMSM). First, a pilot survey is made to investigate the typical harmonics in the line currents of PMSM. Second, an appropriate structure of observer is formulated with the input…
Read MoreFetal Electrocardiogram Extraction using Moth Flame Optimization (MFO)-Based Adaptive Filter
Effective Fetal Electrocardiogram (FECG) Extraction provides medical workers with precise knowledge for monitoring fetal health condition during gestational age. However, Fetal ECG Extraction still remains a challenge as the signal is weak and contaminated with noises of different kinds, more significantly maternal ECG. In this work, a new Moth Flame optimization algorithm (MFO)-based adaptive filter…
Read MoreAutomated Extraction of Heavyweight and Lightweight Models of Urban Features from LiDAR Point Clouds by Specialized Web-Software
3D city modeling may be considered as one of the key applications, that are provided by the Automated Feature Extraction (AFE) techniques from LiDAR data. The authors attempt to prove that with growing availability of LiDAR surveying methods the resulted 3D city models become the most significant modeled features for any urban environment. Our paper…
Read MoreEye Feature Extraction with Calibration Model using Viola-Jones and Neural Network Algorithms
This paper presents the setup of eye tracking calibration methodology and the preliminary test results of the training model from the eye tracking data. Eye tracking requires good accuracy from the calibration process of the human eyes feature extraction from facial region. Viola-Jones algorithm is applied for this purpose by using Haar Basic feature filters…
Read MoreMulti Biometric Thermal Face Recognition Using FWT and LDA Feature Extraction Methods with RBM DBN and FFNN Classifier Algorithms
Person recognition using thermal imaging, multi-biometric traits, with groups of feature filters and classifiers, is the subject of this paper. These were used to tackle the problems of biometric systems, such as a change in illumination and spoof attacks. Using a combination of, hard and soft-biometric, attributes in thermal facial images. The hard-biometric trait, of…
Read MoreApplication of Feature Extraction for Breast Cancer using One Order Statistic, GLCM, GLRLM, and GLDM
The increasing number of breast cancer in recent years has attracted numerous researchers’ attention. Several techniques of Computer Aided Diagnosis System have been proposed as alternative solutions to diagnose breast cancer. The flaw of simply using the naked eye to see the differences between normal and with cancer mammogram images makes the texture analysis play…
Read MoreA Relation Extraction System for Indian Languages
Relation Extraction is an important subtask of Information Extraction that involves extracting significant facts from natural language text. Extracting structured information from the plaintext is the ultimate goal of IE systems. The Indian language content on the internet is increasing day to day. Extracting relevant information from this huge unstructured data is a challenging task…
Read MoreA Machine Learning Framework Using Distinctive Feature Extraction for Hand Gesture Recognition
There are more than 7billion people in the world where there are around 500 million people in the world who are denied from normal lifestyle due to physical and mental issue. It is completely fair to say that every person deserves to enjoy a normal lifestyle. While physically and mentally challenged people find suitable way…
Read MoreDomain Independent Feature Extraction using Rule Based Approach
Sentiment analysis is one of the most popular information extraction tasks both from business and research prospective. From the standpoint of research, sentiment analysis relies on the methods developed for natural language processing and information extraction. One of the key aspects of it is the opinion word lexicon. Product’s feature from online reviews is an…
Read MoreEfficient Pattern Recognition Resource Utilization Neural Network
Neural Networks derives intelligent systems and modern autonomous applications. With the complexity introduced in today’s systems, designing architectures remains open research problem in all fields. Despite many efforts to generalize, the resources required by neural architectures remain challenge. Robots design, Smart cities, IoTs …etc. become the leading industry and driving the fourth industrial revolutions. All…
Read MoreBeyond Fitness: Revolutionary Exercise Tracker Combining Pose Recognition with Heart Rate Monitoring using Remote Photoplethysmography (rPPG)
Heart rate (HR) is a critical indicator in fitness monitoring, athletic performance evaluation, and injury prevention. However, traditional motion-sensitive wearable devices are highly susceptible to movement artifacts, which degrade measurement accuracy during physical activity. Remote photoplethysmography (rPPG) offers a non-contact alternative for HR measurement, though it too remains sensitive to motion. This study proposes a…
Read MoreText Line Segmentation on Myanmar Handwritten Document using Average Linkage Clustering Algorithm
Text line segmentation from document images is a significant challenge in the field of document image analysis. It involves extracting individual text lines from Myanmar handwritten document images to enable text recognition. This task becomes particularly challenging in Myanmar handwritten documents, especially those with irregular or cursive writing styles, due to variations in line spacing,…
Read MoreAdvancements in Explainable Artificial Intelligence for Enhanced Transparency and Interpretability across Business Applications
This manuscript offers an in-depth analysis of Explainable Artificial Intelligence (XAI), em- phasizing its crucial role in developing transparent and ethically compliant AI systems. It traces AI’s evolution from basic algorithms to complex systems capable of autonomous de- cisions with self-explanation. The paper distinguishes between explainability—making AI decision processes understandable to humans—and interpretability, which provides…
Read MoreFrom Sensors to Data: Model and Architecture of an IoT Public Network
RetePAIoT of Emilia-Romagna region is an IoT Public Network, financed by Emilia-Romagna Region and developed by Lepida Scpa, where citizens, private companies and Public Administrations can integrate free of charge their own sensors of any type and anywhere in the region. The main objective of the project is to provide a facility to implement the…
Read MoreAn Ensemble of Voting- based Deep Learning Models with Regularization Functions for Sleep Stage Classification
Sleep stage performs a vital role in people’s daily lives in the detection of sleep-related diseases. Conventional automated sleep stage classifier models are not efficient due to the complexity linked to the design of mathematical models and extraction of hand-engineering features. Further, quick oscillations amongst sleep stages frequently lead to indistinct feature extraction, which might…
Read MoreTransfer and Ensemble Learning in Real-time Accurate Age and Age-group Estimation
Aging is considered to be a complex process in almost every species’ life, which can be studied at a variety of levels of abstraction as well as in different organs. Not surprisingly, biometric characteristics from facial images play a significant role in predicting human’s age. Specifically, automatic age estimation in real-time situation has begun to…
Read MoreAssociation Rules for Knowledge Discovery From E-News Articles: A Review of Apriori and FP-Growth Algorithms
Owing to technological development, the internet has become the world’s largest platform where an unaccountable amount of e-news information is freely available to use. Most of the time, e-newspaper readers have to examine the massive collection of e-news articles to locate necessary information relevant to them. Massive semi-structured and unstructured texts usually mislead the readers…
Read MoreAn Alternative Approach for Thai Automatic Speech Recognition Based on the CNN-based Keyword Spotting with Real-World Application
An automatic speech recognition (ASR) is a key technology for preventing an ongoing global coronavirus epidemic. Due to the limited corpus database and the morphological diversity of the Thai language, Thai speech recognition is still difficult. In this research, the automatic speech recognition model was built differently from the traditional Thai NLP systems by using…
Read MoreHiding Information in DNA Sequence Data using Open Reading Frame Guided Splicing
Encouraged by the huge publicly available genomic databases, research in the field of steganography was recently extended to utilize DNA sequence data to conceal secret information. As an extension of the work presented earlier by the author, this paper proposes an approach for a secure data communication channel between two parties. At one side of…
Read MorePerformance Evaluation of Convolutional Neural Networks (CNNs) And VGG on Real Time Face Recognition System
Face Recognition (FR) is considered as a heavily studied topic in computer vision field. The capability to automatically identify and authenticate human’s faces using real-time images is an important aspect in surveillance, security, and other related domains. There are separate applications that help in identifying individuals at specific locations which help in detecting intruders. The…
Read MoreDetection and Counting of Fruit Trees from RGB UAV Images by Convolutional Neural Networks Approach
The use of Unmanned Aerial Vehicle (UAV) can contribute to find solutions and add value to several agricultural problems, favoring thus productivity, better quality control processes and flexible farm management. In addition, the strategies that allow the acquisition and analysis of data from agricultural environments can help optimize current practices such as crop counting. The…
Read MoreConvolutional Neural Network Based on HOG Feature for Bird Species Detection and Classification
This work is concerned with the detection and classification of birds that have applications like monitoring extinct and migrated birds. Recent computer vision algorithms can precise this kind of task but still there are some dominant issues like low light, very little differences between subspecies of birds, etc are to be studied. As Convolution Neural…
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